Data on molecular docking and molecular dynamics targeting Mycobacterium tuberculosis shikimic acid kinase

We have previously performed a hierarchical in silico screening of a Mycobacterium tuberculosis shikimic acid kinase [1]. Specifically, 11 compounds were screened from a library of 154,118 compounds provided by ChemBridge [2] using UCSF DOCK [3] and the GOLD [4] program in the first and second steps, respectively. Molecular dynamic simulations were further performed on compound 2 (2-[(5Z)-5-(1-benzyl-5bromo-2-oxoindol-3-(5Z)-5-(1-benzyl-5-bromo-2-oxoindol-3-(5Z)-4-oxo-2 ylidene)-4oxo-2-sulfanylidene-1,3-thiazolidin-3-yl] acetic acid), which showed antimicrobial efficacy. These processes yielded ligand docking scores and trajectories. In this data article, we have added solvent-accessible surface area and PCA analyses, which were calculated from the raw docking scores and trajectories. Data obtained from molecular docking and molecular dynamic simulations are useful in two ways: (1) Further support for previous work (2) Provides a stepping stone for experimental scientists to conduct in silico studies and research ideas for other drug discovery researchers and computational biologists. We believe that this article will provide an opportunity to develop new Mycobacterium tuberculosis therapeutics through searching for analogs and inhibitors against new targets.

Identification of two novel chemical classes of Autotaxin (ATX) inhibitors using Enalos Asclepios KNIME nodes

Autotaxin is a secreted lysophospholipase D which is a member of the ectonucleotide pyrophosphatase/phosphodiesterase family converting extracellular lysophosphatidylcholine and other non-choline lysophospholipids, such as lysophosphatidylethanolamine and lysophosphatidylserine, to the lipid mediator lysophosphatidic acid. Autotaxin is implicated in various fibroproliferative diseases including interstitial lung diseases, such as idiopathic pulmonary fibrosis and hepatic fibrosis, as well as in cancer. In this study, we present an effort of identifying ATX inhibitors that bind to allosteric ATX binding sites using the Enalos Asclepios KNIME Node. All the available PDB crystal structures of ATX were collected, prepared, and aligned. Visual examination of these structures led to the identification of four crystal structures of human ATX co-crystallized with four known inhibitors. These inhibitors bind to five binding sites with five different binding modes. These five binding sites were thereafter used to virtually screen a compound library of 14,000 compounds to identify molecules that bind to allosteric sites. Based on the binding mode and interactions, the docking score, and the frequency that a compound comes up as a top-ranked among the five binding sites, 24 compounds were selected for in vitro testing. Finally, two compounds emerged with inhibitory activity against ATX in the low micromolar range, while their mode of inhibition and binding pattern were also studied. The two derivatives identified herein can serve as "hits" towards developing novel classes of ATX allosteric inhibitors.

In Silico Screening and Experimental Verification of Near-Infrared-Emissive Two-Boron-Doped Polycyclic Aromatic Hydrocarbons

Embedding two boron atoms into a polycyclic aromatic hydrocarbon (PAH) leads to the formation of a neutral analogue that is isoelectronic to the corresponding dicationic PAH skeleton, which can significantly alter its electronic structure. Based on this concept, we explore herein the identification of near-infrared (NIR)-emissive PAHs with the aid of an in silico screening method. Using perylene as the PAH scaffold, we embedded two boron atoms and fused two thiophene rings to it. Based on this design concept, all possible structures (ca. 2500 entities) were generated using a comprehensive structure generator. Time-dependent DFT calculations were conducted on all these structures, and promising candidates were extracted based on the vertical excitation energy, transition dipole moment, and atomization energy per bond. One of the extracted dithieno-diboraperylene candidates was synthesized and indeed exhibited emission at 724 nm with a quantum yield of 0.40 in toluene, demonstrating the validity of this screening method. This modification was further applied to other PAHs, and a series of thienobora-modified PAHs was synthesized.

Effects of fermentation with Lactiplantibacillus plantarum NCU116 on the antihypertensive activity and protein structure of black sesame seed

Effects of fermentation by Lactobacillus Plantarum NCU116 on the antihypertensive potential of black sesame seed (BSS) and structure characteristics of fermented black sesame seed protein (FBSSP) were investigated. Angiotensin-I-converting enzyme (ACE) inhibition and zinc chelating ability of fermented black sesame seed hydrolysate (FBSSH) reached the highest of 60.78 ± 3.67 % and 2.93 ± 0.04 mg/mL at 48 h and 60 h of fermentation, respectively. Additionally, the antioxidant activities of FBSSH and surface hydrophobicity of FBSSP were increased noticeably by fermentation. The α-helix and β-rotation of FBSSP tended to decrease and increase, respectively, during fermentation. Correlation analysis indicated strong positive relationships between β-turn and ACE inhibition activity as well as zinc chelating ability with correlation coefficients r of 0.8976 and 0.8932. Importantly, novel ACE inhibitory peptides LLLPYY (IC50 = 12.20 μM) and ALIPSF (IC50 = 558.99 μM) were screened from FBSSH at 48 h using in silico method. Both peptides showed high antioxidant activities in vitro. Molecular docking analysis demonstrated that the hydrogen bond connected with zinc ions of ACE mainly attributed to the potent ACE inhibitory activity of LLLPYY. The findings indicated that fermentation by Lactobacillus Plantarum NCU116 is an effective method to enhance the antihypertensive potential of BSS.

Two novel angiotensin I-converting enzyme inhibitory peptides from garlic protein: In silico screening, stability, antihypertensive effects in vivo and underlying mechanisms

This study aimed to screen novel angiotensin I-converting enzyme (ACE) inhibitory peptides from garlic proteins and to explore their underlying antihypertensive mechanisms in vivo. After simulated hydrolysis and in silico screening, two novel peptides (MGR and HDCF) were obtained with the highest ACE inhibitory activity (IC50 of 4.50 μM and 26.38 μM) and acted as competitive inhibitors. They interacted with key residues in the ACE receptor mainly through hydrogen bonding and exhibited excellent stability against high temperature, extreme pH, and gastrointestinal digestion. In spontaneously hypertensive rats, MGR and HDCF effectively lowered blood pressure after single or continuous treatments. This was mainly achieved by balancing the renin-angiotensin system, improving renal and cardiac impairment, and regulating endothelial dysfunction. These findings suggested that garlic proteins were potentially suitable materials to prepare ACE inhibitory peptides and provided two promising candidates for ACE inhibition as functional food ingredients.

Discovery of furopyridine-based compounds as novel inhibitors of Janus kinase 2: In silico and in vitro studies

Janus kinase 2 (JAK2), one of the JAK isoforms participating in a JAK/STAT signaling cascade, has been considered a potential clinical target owing to its critical role in physiological processes involved in cell growth, survival, development, and differentiation of various cell types, especially immune and hematopoietic cells. Substantial studies have proven that the inhibition of this target could disrupt the JAK/STAT pathway and provide therapeutic outcomes for cancer, immune disorders, inflammation, and COVID-19. Herein, we performed docking-based virtual screening of 63 in-house furopyridine-based compounds and verified the first-round screened compounds by in vitro enzyme- and cell-based assays. By shedding light on the integration of both in silico and in vitro methods, we could elucidate two promising compounds. PD19 showed cytotoxic effects on human erythroblast cell lines (TF-1 and HEL) with IC50 values of 57.27 and 27.28 μM, respectively, while PD12 exhibited a cytotoxic effect on TF-1 with an IC50 value of 83.47 μM by suppressing JAK2/STAT5 autophosphorylation. In addition, all screened compounds were predicted to meet drug-like criteria based on Lipinski's rule of five, and none of the extreme toxicity features were found. Molecular dynamic simulations revealed that PD12 and PD19 could form stable complexes with JAK2 in an aqueous environment, and the van der Waals interactions were the main force driving the complex formation. Besides, all compounds sufficiently interacted with surrounding amino acids in all crucial regions, including glycine, catalytic, and activation loops. Altogether, PD12 and PD19 identified here could potentially be developed as novel therapeutic inhibitors disrupting the JAK/STAT pathway.

An efficient and universal In silico screening strategy for acquisition of high-affinity Aptamer and its application in analytical utility

Numerous aptamers against various targets have been identified through the technology of systematic evolution of ligands by exponential enrichment (SELEX), but the affinity of these aptamers are often insufficient due to the limitations of SELEX. Therefore, a more rational in silico screening strategy (ISS) was developed for efficient screening of high affinity aptamers, which took shape complementarity and thermodynamic stability into consideration. Neuron specific enolase (NSE), a tumor marker, was selected as the target molecule. In the screening process, three aptamer candidates with good shape complementarity, lower ΔG values, and higher ZDOCK scores were produced. The dissociation constant (Kd) of these candidates to NSE was determined to be 10.13 nM, 14.82 nM, and 2.76 nM, respectively. Each of them exhibited higher affinity to NSE than the parent aptamer (Kd = 23.83 nM). Finally, an antibody-free fluorescence aptasensor assay, based on the aptamer with the highest affinity, P-5C8G, was conducted, resulting in a limit of detection (LOD) value of 1.8 nM, which was much lower than the parental aptamer (P, LOD = 12.6 nM). The proposed ISS approach provided an efficient and universal strategy to improve the aptamer to have a high affinity and good analytical utility.

Identification, characterization, and insights into the mechanism of novel dipeptidyl peptidase-IV inhibitory peptides from yak hemoglobin by in silico exploration, molecular docking, and in vitro assessment

Dipeptidyl peptidase IV (DPP-IV) inhibitory peptides were screened and identified from yak hemoglobin for the first time by in silico analysis, molecular docking, and in vitro evaluation. Results showed that yak hemoglobin had a high potential to produce DPP-IV inhibitory peptides based on the sequence alignment and bioactive potential evaluation. Furthermore, "pancreatic elastase + stem bromelain" was the optimal combined-enzymatic strategy by simulated proteolysis. Additionally, 25 novel peptides were found from its simulated hydrolysate, among which 10 peptides had high binding affinities with DPP-IV by molecular docking. Most of these peptides were also in silico characterized with favorable physicochemical properties and biological potentials, including relatively low molecular weight, high hydrophobicity, several net charges, good water solubility, nontoxicity, acceptable sensory quality, and good human intestinal absorption. Finally, six novel DPP-IV inhibitory peptides were identified via in vitro assessment, among which EEKA (IC50 = 235.26 μM), DEV (IC50 = 339.45 μM), and HCDKL (IC50 = 632.93 μM) showed the strongest capacities. The hydrogen bonds and electrostatic attractions formed with core residues within the S2 pocket of DPP-IV could be mainly responsible for their inhibition performances. This work provided a time-saving method and broadened application for yak by-products development as sources of functional foods.

Repurposed drugs in combinations exert additive anti-chikungunya virus activity: an in-vitro study

Chikungunya virus (CHIKV) infection causes chikungunya, a viral disease that currently has no specific antiviral treatment. Several repurposed drug candidates have been investigated for the treatment of the disease. In order to improve the efficacy of the known drugs, combining drugs for treatment is a promising approach. The current study was undertaken to explore the antiviral activity of a combination of repurposed drugs that were reported to have anti-CHIKV activity. We explored the effect of different combinations of six effective drugs (2-fluoroadenine, emetine, lomibuvir, enalaprilat, metyrapone and resveratrol) at their non-toxic concentrations against CHIKV under post infection treatment conditions in Vero cells. Focus-forming unit assay, real time RT-PCR, immunofluorescence assay, and western blot were used to determine the virus titre. The results revealed that the combination of 2-fluoroadenine with either metyrapone or emetine or enalaprilat exerted inhibitory activity against CHIKV under post-infection treatment conditions. The effect of these drug combinations was additive in nature compared to the effect of the individual drugs. The results suggest an additive anti-viral effect of these drug combinations against CHIKV. The findings could serve as an outline for the development of an innovative therapeutic approach in the future to treat CHIKV-infected patients.

Computer-Aided Drug Discovery and Design: Recent Advances and Future Prospects

Computer-aided drug discovery and design involve the use of information technologies to identify and develop, on a rational ground, chemical compounds that align a set of desired physicochemical and biological properties. In its most common form, it involves the identification and/or modification of an active scaffold (or the combination of known active scaffolds), although de novo drug design from scratch is also possible. Traditionally, the drug discovery and design processes have focused on the molecular determinants of the interactions between drug candidates and their known or intended pharmacological target(s). Nevertheless, in modern times, drug discovery and design are conceived as a particularly complex multiparameter optimization task, due to the complicated, often conflicting, property requirements.This chapter provides an updated overview of in silico approaches for identifying active scaffolds and guiding the subsequent optimization process. Recent groundbreaking advances in the field have also analyzed the integration of state-of-the-art machine learning approaches in every step of the drug discovery process (from prediction of target structure to customized molecular docking scoring functions), integration of multilevel omics data, and the use of a diversity of computational approaches to assist target validation and assess plausible binding pockets.

Identification of antioxidant peptides targeting Keap1-Nrf2-ARE pathway from in vitro digestion of pork sausage with partial substitution of NaCl by KCl

The Kelch-like ECH-associated protein 1 (Keap1)-nuclear factor erythroid 2-related factor 2 (Nrf2)-antioxidant response elements (ARE) pathway is one of the most important cellular defense mechanisms against oxidative stress. This study focuses on finding antioxidant peptides from in vitro digestion products of pork sausage with partial substitution of NaCl by KCl by virtual screening. Six antioxidant peptides, LIVGFPAYGH, DWWGSTVR, WNSLLIR, IVGFPAYGH, FDNLWDQGL, and LRSPSWDPF, could activate the Keap1-Nrf2-ARE pathway and protect cells from oxidative stress. DWWGSTVR exhibits the most robust activity among them. Further studies indicated that DWWGSTVR could increase the expression of many antioxidant enzymes by enabling the transfer of Nrf2 from the cytoplasm to the nucleus. In summary, these six peptides are proven to be Nrf2 activators and could be used as functional foods to prevent and treat various oxidative stress-induced diseases.

A first-in-class dimethyl 2-acetamido terephthalate inhibitor targeting Conyza canadensis SHMT1 with a novel herbicidal mode-of-action

INTRODUCTION

Herbicide application is a highly efficiency method of weed control that boots agricultural output and assures food security. The development of novel herbicides focuses on improved bioactivity and new modes of action. The amino acid biosynthesis was validated as a promising novel mode of action for herbicidal compounds. However, the amino acid biosynthesis enzyme remains largely unexplored for herbicidal targets.

OBJECTIVES

Serine hydroxymethyl transferase (SHMT) is an essentialenzyme in the photorespiratory cycle. The study aims to explore Conyza canadensis SHMT1 (CcSHMT1) as a promising target for herbicide discovery.

METHODS

Structure determination of CcSHMT1 was resolved by X-ray crystallography. Virtual screening docking experiments were performed with Glide version 5.5. Novel derivatives of dimethyl 2-acetamido terephthalate were further designed, synthesized, and bioassay. The druggability of the inhibitor was evidenced by ultrastructural changes in mitochondria, in vivo and vitro enzyme activity assays, and genetics analysis.

RESULTS

CcSHMT1 has a typical PLP-dependent enzyme 3D structure. The dimethyl 2-acetamido terephthalate-containing compounds had herbicidal activity. Dimethyl 2-(2-(4-(2-(4-bromo-2-chlorophenoxy) acetyl)piperazin-1-yl)acetamido) terephthalate (Compound 9ay, EC50 = 193.8 g a.i./ ha) exhibited the highest herbicidal activity on tested weed among the synthesized compounds. Compound 9ay had no obvious adverse effect on the growth of maize and honeybees. Compound 9ay was verified to target CcSHMT1 as an herbicide candidate.

CONCLUSION

A first-in-class CcSHMT1 inhibitor that could be developed as a potent herbicide with a new mode of action and provide an avenue for discovering novel inhibitors of pyridoxal-5-phosphate-dependent enzymes.

Novel drug transporter substrates identification: An innovative approach based on metabolomic profiling, in silico ligand screening and biological validation

Solute carrier (SLC) transport proteins are fundamental for the translocation of endogenous compounds and drugs across membranes, thus playing a critical role in disease susceptibility and drug response. Because only a limited number of transporter substrates are currently known, the function of a large number of SLC transporters is elusive. Here, we describe the proof-of-concept of a novel strategy to identify SLC transporter substrates exemplarily for the proton-coupled peptide transporter (PEPT) 2 (SLC15A2) and multidrug and toxin extrusion (MATE) 1 transporter (SLC47A1), which are important renal transporters of drug reabsorption and excretion, respectively. By combining metabolomic profiling of mice with genetically-disrupted transporters, in silico ligand screening and in vitro transport studies for experimental validation, we identified nucleobases and nucleoside-derived anticancer and antiviral agents (flucytosine, cytarabine, gemcitabine, capecitabine) as novel drug substrates of the MATE1 transporter. Our data confirms the successful applicability of this new approach for the identification of transporter substrates in general, which may prove particularly relevant in drug research.

A small molecule targeting the interaction between human papillomavirus E7 oncoprotein and cellular phosphatase PTPN14 exerts antitumoral activity in cervical cancer cells

Human papillomavirus (HPV)-induced cancers still represent a major health issue for worldwide population and lack specific therapeutic regimens. Despite substantial advancements in anti-HPV vaccination, the incidence of HPV-related cancers remains high, thus there is an urgent need for specific anti-HPV drugs. The HPV E7 oncoprotein is a major driver of carcinogenesis that acts by inducing the degradation of several host factors. A target is represented by the cellular phosphatase PTPN14 and its E7-mediated degradation was shown to be crucial in HPV oncogenesis. Here, by exploiting the crystal structure of E7 bound to PTPN14, we performed an in silico screening of small-molecule compounds targeting the C-terminal CR3 domain of E7 involved in the interaction with PTPN14. We discovered a compound able to inhibit the E7/PTPN14 interaction in vitro and to rescue PTPN14 levels in cells, leading to a reduction in viability, proliferation, migration, and cancer-stem cell potential of HPV-positive cervical cancer cells. Mechanistically, as a consequence of PTPN14 rescue, treatment of cancer cells with this compound altered the Yes-associated protein (YAP) nuclear-cytoplasmic shuttling and downstream signaling. Notably, this compound was active against cervical cancer cells transformed by different high-risk (HR)-HPV genotypes indicating a potential broad-spectrum activity. Overall, our study reports the first-in-class inhibitor of E7/PTPN14 interaction and provides the proof-of-principle that pharmacological inhibition of this interaction by small-molecule compounds could be a feasible therapeutic strategy for the development of novel antitumoral drugs specific for HPV-associated cancers.

A polo-like kinase inhibitor identified by computational repositioning attenuates pulmonary fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is a fatal fibrotic lung disease with few effective therapeutic options. Recently, drug repositioning, which involves identifying novel therapeutic potentials for existing drugs, has been popularized as a new approach for the development of novel therapeutic reagents. However, this approach has not yet been fully utilized in the field of pulmonary fibrosis.

METHODS

The present study identified novel therapeutic options for pulmonary fibrosis using a systematic computational approach for drug repositioning based on integration of public gene expression signatures of drug and diseases (in silico screening approach).

RESULTS

Among the top compounds predicted to be therapeutic for IPF by the in silico approach, we selected BI2536, a polo-like kinase (PLK) 1/2 inhibitor, as a candidate for treating pulmonary fibrosis using an in silico analysis. However, BI2536 accelerated mortality and weight loss rate in an experimental mouse model of pulmonary fibrosis. Because immunofluorescence staining revealed that PLK1 expression was dominant in myofibroblasts while PLK2 expression was dominant in lung epithelial cells, we next focused on the anti-fibrotic effect of the selective PLK1 inhibitor GSK461364. Consequently, GSK461364 attenuated pulmonary fibrosis with acceptable mortality and weight loss in mice.

CONCLUSIONS

These findings suggest that targeting PLK1 may be a novel therapeutic approach for pulmonary fibrosis by inhibiting lung fibroblast proliferation without affecting lung epithelial cells. In addition, while in silico screening is useful, it is essential to fully determine the biological activities of candidates by wet-lab validation studies.

Repurposing of potential antiviral drugs against RNA-dependent RNA polymerase of SARS-CoV-2 by computational approach

The high incidences of COVID-19 cases are believed to be associated with high transmissibility rates, which emphasizes the need for the discovery of evidence-based antiviral therapies for curing the disease. The rationale of repurposing existing classes of antiviral small molecule therapeutics against SARS-CoV-2 infection has been expected to accelerate the tedious and expensive drug development process. While Remdesivir has been recently approved to be the first treatment option for specific groups of COVID-19 patients, combinatory therapy with potential antiviral drugs may be necessary to enhance the efficacy in different populations. Hence, a comprehensive list of investigational antimicrobial drug compounds such as Favipiravir, Fidaxomicin, Galidesivir, GC376, Ribavirin, Rifabutin, and Umifenovir were computationally evaluated in this study. We performed in silico docking and molecular dynamics simulation on the selected small molecules against RNA-dependent RNA polymerase, which is one of the key target proteins of SARS-CoV-2, using AutoDock and GROMACS. Interestingly, our results revealed that the macrocyclic antibiotic, Fidaxomicin, possesses the highest binding affinity with the lowest energy value of -8.97 kcal/mol binding to the same active sites of RdRp. GC376, Rifabutin, Umifenovir and Remdesivir were identified as the next best compounds. Therefore, the above-mentioned compounds could be considered good leads for further preclinical and clinical experimentations as potentially efficient antiviral inhibitors for combination therapies against SARS-CoV-2.

In Silico Screening of Off-line Comprehensive Two-Dimensional Counter-current Chromatography with Liquid Chromatography for Four Saponins Isolation

Be restrained by the limited peak capacity, one dimension chromatography usually leads to an unsatisfactory separation with low purity of compounds in a complex mixture. To obtain more highly pure targets for standard reference and to discover new substances for structural elucidation, two-dimensional chromatography is more and more prevalent in many fields. As few metrics on assessment of preparative capability of two-dimensional chromatographic separations is reported, a methodology of in silico screening of various two-dimensional chromatographic separations with a minimal number of experiments was demonstrated in this work, which was based on three descriptors including the occupation rate of peaks and system homogeneity of a two-dimensional separation space, and the minimal distance of all nearest-neighbor distances of peaks. Combining the advantages of counter-current chromatography and liquid chromatography, we elaborated the methodology by employing off-line comprehensive two-dimensional counter-current chromatography with liquid chromatography to be in silico screened for separation of four saponins from Panax notoginseng at analytical scale to simulate the case of preparative scale transfer. The predictive results were presented by two-dimensional contour plots and verified by experiments. The result showed that the experimental results were in general accord with the predictive results. This article is protected by copyright. All rights reserved.

In silico drug repurposing for coronavirus (COVID-19): screening known HCV drugs against the SARS-CoV-2 spike protein bound to angiotensin-converting enzyme 2 (ACE2) (6M0J)

In this study, FDA-approved HCV antiviral drugs and their structural analogues—several of them in clinical trials—were tested for their inhibitory properties toward the SARS-CoV-2 spike protein bound to angiotensin-converting enzyme 2 (6M0J) using a virtual screening approach and computational chemistry methods. The most stable structures and the corresponding binding affinities of thirteen such antiviral compounds were obtained. Frontier molecular orbital theory, global reactivity descriptors, molecular docking calculations and electrostatic potential analysis were used to hypothesize the bioactivity of these drugs against 6M0J. It is found that an increased affinity for the protein is shown by inhibitors with large compound volume, relatively higher electrophilicity index, aromatic rings and heteroatoms that participate in hydrogen bonding. Among the tested drugs, four compounds 10–13 showed excellent results—binding affinities − 11.2 to − 11.5 kcal mol⁻¹. These four top scoring compounds may act as lead compounds for further experimental validation, clinical trials and even for the development of more potent antiviral agents against the SARS-CoV-2.

In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli

Abstract

Sequence-based screening has been widely applied in the discovery of novel microbial enzymes. However, majority of the sequences in the genomic databases were annotated using computational approaches and lacks experimental characterization. Hence, the success in obtaining the functional biocatalysts with improved characteristics requires an efficient screening method that considers a wide array of factors. Recombinant expression of microbial enzymes is often hampered by the undesirable formation of inclusion body. Here, we present a systematic in silico screening method to identify the proteins expressible in soluble form and with the desired biological properties. The screening approach was adopted in the recombinant expression of dimethyl sulfide (DMS) monooxygenase in Escherichia coli. DMS monooxygenase, a two-component enzyme consisting of DmoA and DmoB subunits, was used as a model protein. The success rate of producing soluble and active DmoA is 71% (5 out of 7 genes). Interestingly, the soluble recombinant DmoA enzymes exhibited the NADH:FMN oxidoreductase activity in the absence of DmoB (second subunit), and the cofactor FMN, suggesting that DmoA is also an oxidoreductase. DmoA originated from Janthinobacterium sp. AD80 showed the maximum NADH oxidation activity (maximum reaction rate: 6.6 µM/min; specific activity: 133 µM/min/mg). This novel finding may allow DmoA to be used as an oxidoreductase biocatalyst for various industrial applications. The in silico gene screening methodology established from this study can increase the success rate of producing soluble and functional enzymes while avoiding the laborious trial and error involved in the screening of a large pool of genes available.

Key points

• A systematic gene screening method was demonstrated.

• DmoA is also an oxidoreductase capable of oxidizing NADH and reducing FMN.

• DmoA oxidizes NADH in the absence of external FMN.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12008-8.

Insights into ultrasound-promoted degradation of naphthenic acid compounds in oil sands process affected water. Part II: In silico quantum screening of hydroxyl radical initiated and propagated degradation of benzoic acid

In Part I, we outlined the importance of sustainable sonochemical treatment to intensify oil sands process affected water (OSPW) treatment empirically and hypothesized degradation pathways. Herein, we elucidate the formation of intermediate products with well-defined molecular level solutions. Proposed mechanisms describe hydroxylation, decarboxylation and bond scission which drive the degradation of intermediates towards mineralization. This comprehensive first study on in silico screening of sonochemical degradation investigates quantum methods using density functional theory to explain the postulated degradation mechanisms through a theoretical radical attack approach, based on condensed Fukui reactivity indicators. A nudged elasticity band (NEB) approach is applied to find a minimum energy path (MEP), allowing the determination of intermediate products and energy barriers associated with naphthenic acid degradation. This approach provides structures and energies of the breakdown compounds formed along the reaction pathway enabling the determination of molecular reaction kinetics. In continuation of Part 1, the focus of this study is to evaluate sonochemically-induced hydroxyl radical (OH^•) reactions of benzoic acid using density functional theory. Hydroxylation and decarboxylation mechanisms of the model naphthenic acid compound and its intermediates were simulated to determine the prospective pathway to ideal mineralization. DFT was applied to calculate interaction energies, Mulliken charges, Hirshfeld population analysis, dipole moments, frontier orbitals, and polarizability. Electronic properties and frontier orbital trends were also compared to computational work by Riahi et al.[1] to confirm the transition states by Nudged Elastic Band Transition State theory (NEB-TS). In combination with Hirshfeld Population analysis, Fukui indices suggest a more linear degradation pathway narrowed down from earlier experimental work by Singla et al.[2]. The linear free energy relationship for the newly suggested computational benzoic acid degradation can be determined by lnk_TST/W=-1.677ΔG-15.41 with a R² of 0.9997 according to classic transition state theory and Wigner tunneling. This computational method can be used to explore possible degradation pathways of other NAs and bridges molecular-to-macroscale sonochemical degradation of NA's through a manifestation of molecular solutions.

Identification and characterization of potent, selective, and efficacious inhibitors of human arylamine N-acetyltransferase 1

Arylamine N-acetyltransferase 1 (NAT1) plays a pivotal role in the metabolism of carcinogens and is a drug target for cancer prevention and/or treatment. A protein-ligand virtual screening of 2 million chemicals was ranked for predicted binding affinity towards the inhibition of human NAT1. Sixty of the five hundred top-ranked compounds were tested experimentally for inhibition of recombinant human NAT1 and N-acetyltransferase 2 (NAT2). The most promising compound 9,10-dihydro-9,10-dioxo-1,2-anthracenediyl diethyl ester (compound 10) was found to be a potent and selective NAT1 inhibitor with an in vitro IC₅₀ of 0.75 µM. Two structural analogs of this compound were selective but less potent for inhibition of NAT1 whereas a third structural analog 1,2-dihydroxyanthraquinone (a compound 10 hydrolysis product also known as Alizarin) showed comparable potency and efficacy for human NAT1 inhibition. Compound 10 inhibited N-acetylation of the arylamine carcinogen 4-aminobiphenyl (ABP) both in vitro and in DNA repair-deficient Chinese hamster ovary (CHO) cells in situ stably expressing human NAT1 and CYP1A1. Compound 10 and Alizarin effectively inhibited NAT1 in cryopreserved human hepatocytes whereas inhibition of NAT2 was not observed. Compound 10 caused concentration-dependent reductions in DNA adduct formation and DNA double-strand breaks following metabolism of aromatic amine carcinogens beta-naphthylamine and/or ABP in CHO cells. Compound 10 inhibited proliferation and invasion in human breast cancer cells and showed selectivity towards tumorigenic versus non-tumorigenic cells. In conclusion, our study identifies potent, selective, and efficacious inhibitors of human NAT1. Alizarin's ability to inhibit NAT1 could reduce breast cancer metastasis particularly to bone.

Therapeutic strategies for identifying small molecules against prion diseases

Prion diseases are fatal neurodegenerative disorders, for which there are no effective therapeutic and diagnostic agents. The main pathological hallmark has been identified as conformational changes of the cellular isoform prion protein (PrP^C) to a misfolded isoform of the prion protein (PrP^Sc). Targeting PrP^C and its conversion to PrP^Sc is still the central dogma in prion drug discovery, particularly in in silico and in vitro screening endeavors, leading to the identification of many small molecules with therapeutic potential. Nonetheless, multiple pathological targets are critically involved in the intricate pathogenesis of prion diseases. In this context, multi-target-directed ligands (MTDLs) emerge as valuable therapeutic approach for their potential to effectively counteract the complex etiopathogenesis by simultaneously modulating multiple targets. In addition, diagnosis occurs late in the disease process, and consequently a successful therapeutic intervention cannot be provided. In this respect, small molecule theranostics, which combine imaging and therapeutic properties, showed tremendous potential to cure and diagnose in vivo prion diseases. Herein, we review the major advances in prion drug discovery, from anti-prion small molecules identified by means of in silico and in vitro screening approaches to two rational strategies, namely MTDLs and theranostics, that have led to the identification of novel compounds with an expanded anti-prion profile.

A heuristic, computer-driven and top-down approach to identify novel bioactive peptides: A proof-of-principle on angiotensin I converting enzyme inhibitory peptides

Bioactive peptides are short peptides (3-20 amino acid residues in length) endowed of specific biological activities. The identification and characterization of bioactive peptides of food origin are crucial to better understand the physiological consequences of food, as well as to design novel foods, ingredients, supplements, and diets to counteract mild metabolic disorders. For this reason, the identification of bioactive peptides is also relevant from a pharmaceutical standpoint. Nevertheless, the systematic identification of bioactive sequences of food origin is still challenging and relies mainly on the so defined "bottom-up" approaches, which rarely results in the total identification of most active sequences. Conversely, "top-down" approaches aim at identifying bioactive sequences with certain features and may be more suitable for the precise identification of very potent bioactive peptides. In this context, this work presents a top-down, computer-assisted and hypothesis-driven identification of potent angiotensin I converting enzyme inhibitory tripeptides, as a proof of principle. A virtual library of 6840 tripeptides was screened in silico to identify potential highly potent inhibitory peptides. Then, computational results were confirmed experimentally and a very potent novel sequence, LMP was identified. LMP showed an IC₅₀ of 15.8 and 6.8 µM in cell-free and cell-based assays, respectively. In addition, a bioinformatics approach was used to search potential food sources of LMP. Yolk proteins were identified as a possible relevant source to analyze in further experiments. Overall, the method presented may represent a powerful and versatile framework for a systematic, high-throughput and top-down identification of bioactive peptides.

Strategies for drug repurposing against coronavirus targets

Repurposing regulatory agency approved drugs and investigational compounds with known safety profiles can significantly fast track the drug development timeline over de novo drug discovery, with lower investment requirements and improved attrition rate. These advantages are vital in any epidemic or pandemic situation, where hospital beds are occupied by patients for whom there is no known treatment. Here we examine drug repurposing in the context of human coronaviruses, SARS-CoV, MERS-CoV, and, in particular, SARS-CoV-2, the virus currently causing a continued widespread pandemic with substantial impacts on public health and economy. The key druggable targets explored were those involved in viral entry, viral replication, and viral-induced ARDS, as well as viral proteases, with a focus on the strategy by which the drugs were repurposed.

Cyclooxygenase-2 Inhibitor Parecoxib Was Disclosed as a PPAR-γ Agonist by In Silico and In Vitro Assay

In a search for effective PPAR-γ agonists, 110 clinical drugs were screened via molecular docking, and 9 drugs, including parecoxib, were selected for subsequent biological evaluation. Molecular docking of parecoxib to the ligand-binding domain of PPAR-γ showed high binding affinity and relevant binding conformation compared with the PPAR-γ ligand/antidiabetic drug rosiglitazone. Per the docking result, parecoxib showed the best PPAR-γ transactivation in Ac2F rat liver cells. Further docking simulation and a luciferase assay suggested parecoxib would be a selective (and partial) PPAR-γ agonist. PPAR-γ activation by parecoxib induced adipocyte differentiation in 3T3-L1 murine preadipocytes. Parecoxib promoted adipogenesis in a dose-dependent manner and enhanced the expression of adipogenesis transcription factors PPAR-γ, C/EBPα, and C/EBPβ. These data indicated that parecoxib might be utilized as a partial PPAR-γ agonist for drug repositioning study.

Target-Based In Silico Screening for Phytoactive Compounds Targeting SARS-CoV-2

Abstract

Coronavirus disease 2019 (COVID-19), resulting from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe and fatal pneumonia along with other life-threatening complications. The COVID-19 pandemic has taken a heavy toll on the healthcare system globally and has hit the economy hard in all affected countries. As a result, there is an unmet medical need for both the prevention and treatment of COVID-19 infection. Several herbal remedies have claimed to show promising clinical results, but the mechanisms of action are not clear. We set out to identify the anti-viral natural products of these herbal remedies that presumably inhibit the life cycle of SARS-CoV-2. Particularly we chose four key SARS-CoV-2 viral enzymes as targets: Papain-like protease, Main protease, RNA dependent RNA polymerase, and 2’-O-ribose methyltransferase, which were subjected to an unbiased in silico screening against a small molecule library of 33,765 compounds originating from herbs and medicinal plants. The small molecules were then ranked based on their free energy of fitting into the “druggable” pockets on the surface of each target protein. We have analyzed the best “fit” molecules and annotated them according to their plant sources and pharmacokinetic properties. Here we present a list of potential anti-viral ingredients of herbal remedies targeting SARS-CoV-2 and explore the potential mechanisms of action of these compounds as a framework for further development of chemoprophylaxis agents against COVID-19.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12539-021-00461-4.

In silico screening and exploration into phenotypic alterations of deleterious oncogenic single nucleotide polymorphisms in HSPB1 gene

A small heat shock protein, HSP27, encoded by HSPB1 gene strongly favors survival, proliferation and metastasis of cancer cells and its expression is dependent on post-translational modifications like phosphorylation. This study performed an extensive in silico screening of 20 deleterious non-synonymous SNPs in the coding region of HSPB1 gene, among which four were identified to be cancer associated. The SNP variant I181S introduced a new phosphorylation site in position 181, which might elevate the protein's activation potential. Emergence of other post-translational modifications was also observed in SNP variants: L144P and E130K.Significant conformational changes were observed in I181S, L144P and E130K SNP variants with respect to wild-type HSP27. These SNPs appear in one among 10⁵ individuals, making them more susceptible towards cancer. This study would therefore, instigate development of novel biomarkers for cancer risk detection and would provide a detailed understanding towards varied cancer susceptibility of human population.

In Silico and In Vitro Studies of Natural Compounds as Human CK2 Inhibitors

BACKGROUND

Casein Kinase 2 (CK2) is a ubiquitous cellular serine-threonine kinase with broad spectrum of substrates. This enzyme is widely expressed in eukaryotic cells and is overexpressed in different human cancers. Thus, the inhibition of CK2 can induce the physiological process of apoptosis leading to tumor cell death.

OBJECTIVES

Selecting natural inhibitors toward the target enzyme using database mining.

METHODS

With our continuous effort to discover new compounds with CK2 inhibitory effect, several commercial natural databases were searched using molecular modeling approach and the selected compounds were evaluated in vitro.

RESULTS

Three compounds were selected as candidates and evaluated in vitro using CK2 holoenzyme, their effect on three cancer cell lines was determined. The selected candidates were weak inhibitors toward the target enzyme, only one compound showed moderate effect on cell viability.

CONCLUSION

Several natural databases were screened, compounds were selected and tested in vitro. Despite the unexpected low inhibitory activity of the tested compounds, this study can help in directing the search of potent CK2 inhibitors and better understand the binding requirements of the ATP competitive inhibitors.

MDock: A Suite for Molecular Inverse Docking and Target Prediction

Molecular docking is commonly used for identification of drug candidates targeting a specified protein of known structure. With the increasing emphasis on drug repurposing over recent decades, molecular inverse docking has been widely applied to prediction of the potential protein targets of a specified molecule. In practice, inverse docking has many advantages, including early supervision of drugs' side effects and toxicity. MDock developed from our laboratory is a protein-ligand docking software based on a knowledge-based scoring function and has numerous applications to lead identification. In addition to its computational efficiency on ensemble docking for multiple protein conformations, MDock is well suited for inverse docking. In this chapter, we focus on introducing the protocol of inverse docking with MDock. For academic users, the MDock package is freely available at http://zoulab.dalton.missouri.edu/mdock.htm .

Identification of filovirus entry inhibitors targeting the endosomal receptor NPC1 binding site

Filoviruses, mainly consisting of Ebola viruses (EBOV) and Marburg viruses (MARV), are enveloped negative-strand RNA viruses which can infect humans to cause severe hemorrhagic fevers and outbreaks with high mortality rates. The filovirus infection is mediated by the interaction of viral envelope glycoprotein (GP) and the human endosomal receptor Niemann-Pick C1 (NPC1). Blocking this interaction will prevent the infection. Therefore, we utilized an In silico screening approach to conduct virtual compound screening against the NPC1 receptor-binding site (RBS). Twenty-six top-hit compounds were purchased and evaluated by in vitro cell based inhibition assays against pseudotyped or replication-competent filoviruses. Two classes (A and U) of compounds were identified to have potent inhibitory activity against both Ebola and Marburg viruses. The IC₅₀ values are in the lower level of micromolar concentrations. One compound (compd-A) was found to have a sub-micromolar IC₅₀ value (0.86 μM) against pseudotyped Marburg virus. The cytotoxicity assay (MTT) indicates that compd-A has a moderate cytotoxicity level but the compd-U has much less toxicity and the CC₅₀ value was about 100 μM. Structure-activity relationship (SAR) study has found some analogs of compd-A and -U have reduced the toxicity and enhanced the inhibitory activity. In conclusion, this work has identified several qualified lead-compounds for further drug development against filovirus infection.

Targeting SARS-CoV-2 Nsp3 macrodomain structure with insights from human poly(ADP-ribose) glycohydrolase (PARG) structures with inhibitors

Arrival of the novel SARS-CoV-2 has launched a worldwide effort to identify both pre-approved and novel therapeutics targeting the viral proteome, highlighting the urgent need for efficient drug discovery strategies. Even with effective vaccines, infection is possible, and at-risk populations would benefit from effective drug compounds that reduce the lethality and lasting damage of COVID-19 infection. The CoV-2 MacroD-like macrodomain (Mac1) is implicated in viral pathogenicity by disrupting host innate immunity through its mono(ADP-ribosyl) hydrolase activity, making it a prime target for antiviral therapy. We therefore solved the structure of CoV-2 Mac1 from non-structural protein 3 (Nsp3) and applied structural and sequence-based genetic tracing, including newly determined A. pompejana MacroD2 and GDAP2 amino acid sequences, to compare and contrast CoV-2 Mac1 with the functionally related human DNA-damage signaling factor poly(ADP-ribose) glycohydrolase (PARG). Previously, identified targetable features of the PARG active site allowed us to develop a pharmacologically useful PARG inhibitor (PARGi). Here, we developed a focused chemical library and determined 6 novel PARGi X-ray crystal structures for comparative analysis. We applied this knowledge to discovery of CoV-2 Mac1 inhibitors by combining computation and structural analysis to identify PARGi fragments with potential to bind the distal ribose and adenosyl pockets of the CoV-2 Mac1 active site. Scaffold development of these PARGi fragments has yielded two novel compounds, PARG-345 and PARG-329, that crystallize within the Mac1 active site, providing critical structure-activity data and a pathway for inhibitor optimization. The reported structural findings demonstrate ways to harness our PARGi synthesis and characterization pipeline to develop CoV-2 Mac1 inhibitors targeting the ADP-ribose active site. Together, these structural and computational analyses reveal a path for accelerating development of antiviral therapeutics from pre-existing drug optimization pipelines.

GRAPE, a greedy accumulated strategy for computational protein engineering

Nature harbors fascinating enzymatic catalysts with high efficiency, chemo-, regio- and stereoselectivity. However, the insufficient stability of the enzymes often prevents their widespread utilization for industrial processes. Not content with the finite repertoire of naturally occurring enzymes, protein engineering holds promises to extend the applications of the improved enzymes with desired physical and catalytic properties. Herein, we devised a computational strategy (greedy accumulated strategy for protein engineering, GRAPE) to enhance the thermostability of enzymes. Through scanning of all point mutations of the structural and evolutionary consensus analysis, a library containing fewer than 100 mutations was established for characterization. After preliminary experimental verification, effective mutations are clustered in a multidimensional physical property space and then accumulated via the greedy algorithm to produce the final designed enzyme. Using the recently reported IsPETase from Ideonella sakaiensis that decomposes PET under ambient temperatures as a starting point, we adopted the GRAPE strategy to come up with a DuraPETase (T_M=77°C, raised by 31°C) which showed drastically enhanced degradation performance (300-fold) on semicrystalline PET films at 40°C.

Forkhead transcription factor O1 (FoxO1) in torafugu pufferfish Takifugu rubripes: Molecular cloning, in vitro DNA binding, and target gene screening in fish metagenome

The fish insulin/insulin-like growth factor (IGF) pathway has weak control over carbohydrate metabolism. To understand the molecular basis for the metabolic diversity, we characterized the forkhead box transcription factor O1A (FoxO1A), a downstream target of the insulin/IGF pathway, in torafugu Takifugu rubripes. The cloned torafugu FoxO1A cDNA contained all conserved features critical for its transcriptional activity and a unique unspliced intron encoding a poly-glutamine stretch. Torafugu FoxO1A showed the IGF-dependent nuclear exclusion and in vitro binding to the well-conserved FoxO1 binding site, DAF-16 binding element (DBE), but failed to bind to the insulin-responsive element by which mammalian FoxO1 mediates insulin effects. The subsequent in silico genomic screening provided a list of 587 potential torafugu FoxO1A target genes containing the DBE. Some carbohydrate metabolic genes regulated by FoxO1 in mammals were not included in the list. We further identified about 250 potential fish FoxO1 target genes by integrating results of the DBE screening against fish metagenome that contained 262 species. Neuronal processes appeared to be the common major function of fish FoxO1, although further annotation of the potential target genes is required. These results provide a part of the molecular basis underlying the weak association between the insulin/IGF pathway and carbohydrate metabolism in fish.

ENNAACT is a novel tool which employs neural networks for anticancer activity classification for therapeutic peptides

The prevalence of cancer as a threat to human life, responsible for 9.6 million deaths worldwide in 2018, motivates the search for new anticancer agents. While many options are currently available for treatment, these are often expensive and impact the human body unfavourably. Anticancer peptides represent a promising emerging field of anticancer therapeutics, which are characterized by favourable toxicity profile. The development of accurate in silico methods for anticancer peptide prediction is of paramount importance, as the amount of available sequence data is growing each year. This study leverages advances in machine learning research to produce a novel sequence-based deep neural network classifier for anticancer peptide activity. The classifier achieves performance comparable to the best-in-class, with a cross-validated accuracy of 98.3%, Matthews correlation coefficient of 0.91 and an Area Under the Curve of 0.95. This innovative classifier is available as a web server at https://research.timmons.eu/ennaact, facilitating in silico screening and design of new anticancer peptide chemotherapeutics by the research community.

In silico structure prediction, molecular docking and dynamic simulation studies on G Protein-Coupled Receptor 116: a novel insight into breast cancer therapy

G Protein-Coupled Receptor gains more importance in cancer research; because of their key role in several physiologic functions of cells. However, most of the GPCR's are orphan receptors, this hampers the finding of drugs against GPCR. G Protein-Coupled Receptor 116 is an adhesion orphan receptor that intensifies the invasion of cells in Triple-Negative Breast Cancer. In this study, existing FDA approved anticancer drugs were chosen as ligands and molecular docking was performed using in silico protein model of GPR116. Molecular interaction was analyzed carefully to identify the crucial amino acids present in binding pocket. Molecular dynamics simulations study executed to verify the structural and dynamic properties of Doxorubicin-GPR116 protein complex. The results have shown that Doxorubicin, Neratinib maleate, Epirubicin, and Lapatinib Ditosylate have good interaction with GPR116 binding site. Tyrosine 195 (Y195), Cysteine 196 (C196), Argenine 197 (R197), and Tryptophan 100 (W100) are commonly found in the majority of ligand-target interaction, hence based on the computational studies selective amino acids might be crucial for functional properties. Further to confirm crucial amino acids, computational mutation studies were executed. Molecular docking analysis with mutated GPR116 disclosed that significant variation in G score compared withligand-native protein interaction. Hence, the theoretical confirmatory structural properties changes support to prove selective crucial amino acids play the significant role in ligand binding. Molecular dynamic simulation results reveal that the interaction was stable throughout the MD simulation. To the best of our prognosis, GPR116 could be the best molecular target for breast cancer drug discovery.Communicated by Ramaswamy H. Sarma.

Transcriptome of Sphaerospora molnari (Cnidaria, Myxosporea) blood stages provides proteolytic arsenal as potential therapeutic targets against sphaerosporosis in common carp

Background

Parasites employ proteases to evade host immune systems, feed and replicate and are often the target of anti-parasite strategies to disrupt these interactions. Myxozoans are obligate cnidarian parasites, alternating between invertebrate and fish hosts. Their genes are highly divergent from other metazoans, and available genomic and transcriptomic datasets are limited. Some myxozoans are important aquaculture pathogens such as Sphaerospora molnari replicating in the blood of farmed carp before reaching the gills for sporogenesis and transmission. Proliferative stages cause a massive systemic lymphocyte response and the disruption of the gill epithelia by spore-forming stages leads to respiratory problems and mortalities. In the absence of a S. molnari genome, we utilized a de novo approach to assemble the first transcriptome of proliferative myxozoan stages to identify S. molnari proteases that are upregulated during the first stages of infection when the parasite multiplies massively, rather than in late spore-forming plasmodia. Furthermore, a subset of orthologs was used to characterize 3D structures and putative druggable targets.

Results

An assembled and host filtered transcriptome containing 9436 proteins, mapping to 29,560 contigs was mined for protease virulence factors and revealed that cysteine proteases were most common (38%), at a higher percentage than other myxozoans or cnidarians (25–30%). Two cathepsin Ls that were found upregulated in spore-forming stages with a presenilin like aspartic protease and a dipeptidyl peptidase. We also identified downregulated proteases in the spore-forming development when compared with proliferative stages including an astacin metallopeptidase and lipases (qPCR). In total, 235 transcripts were identified as putative proteases using a MEROPS database. In silico analysis of highly transcribed cathepsins revealed potential drug targets within this data set that should be prioritised for development.

Conclusions

In silico surveys for proteins are essential in drug discovery and understanding host-parasite interactions in non-model systems. The present study of S. molnari’s protease arsenal reveals previously unknown proteases potentially used for host exploitation and immune evasion. The pioneering dataset serves as a model for myxozoan virulence research, which is of particular importance as myxozoan diseases have recently been shown to emerge and expand geographically, due to climate change.

Design, synthesis, and biological evaluation of tetrahydroquinolin derivatives as potent inhibitors of CBP bromodomain

CREB-binding protein (CBP) is a large multi-domain protein containing a HAT domain catalyzing transacetylation and a bromodomain responsible for acetylated lysine recognition. CBPs could act as transcription co-activators to regulate gene expression and have been shown to play a significant role in the development and progression of many cancers. Herein, through in silico screening two hit compounds with tetrahydroquinolin methyl carbamate scaffold were discovered, among which DC-CPin7 showed an in vitro inhibitory activity with the TR-FRET IC₅₀ value of 2.5 ± 0.3 μM. We obtained a high-resolution co-crystal structure of the CBP bromodomain in complex with DC-CPin7 to guide following structure-based rational drug design, which yielded over ten DC-CPin7 derivatives with much higher potency, among which DC-CPin711 showed approximately 40-fold potency compared with hit compound DC-CPin7 with an in vitro TR-FRET IC₅₀ value of 63.3 ± 4.0 nM. Notably, DC-CPin711 showed over 150-fold selectivity against BRD4 bromodomains. Moreover, DC-CPin711 showed micromolar level of anti-leukemia proliferation through G1 phase cell cycle arrest and cell apoptosis. In summary, through a combination of computational and crystal-based structure optimization, DC-CPin711 showed potent in vitro inhibitory activities to CBP bromodomain with a decent selectivity towards BRD4 bromodomains and good cellular activity to leukemia cells, which could further be applied to related biological and translational studies as well as serve as a lead compound for future development of potent and selective CBP bromodomain inhibitors.

Drug repurposing approach to target FtsZ cell division protein from Salmonella Typhi

Drug repurposing is an efficient alternative approach to counter the increasing drug-resistant pathogens to treat infectious diseases. FtsZ is an essential bacterial cytokinesis protein involved in the formation of cell-division complex and targeting FtsZ using FDA approved drugs is a promising strategy to identify and develop a new antibacterial drug. Using in silico pharmacophore-based screening of drug bank, molecular docking and molecular dynamics simulations, we identified six drugs inhibiting the function of stFtsZ from Salmonella Typhi. The selected drugs target stFtsZ at the hydrophobic cleft formed between the C-terminal domain and helix α7 with binding energy better than -8 kcal/mol. Out of these six drugs, benzethonium chloride showed promising results at 8 μM concentration where it inhibits stFtsZ GTPase activity by 80% and prevents polymerization. Benzethonium chloride also possesses an excellent antibacterial activity against the bacterial culture of Salmonella Typhi (ATCC 19430), Staphylococcus aureus (ATCC 43300) and Escherichia coli (ATCC 25922) with the MIC values of 8 μg/mL, 1 μg/mL and 12 μg/mL, respectively. Based on our current study, the scaffold of benzethonium chloride can be used for the development of broad-spectrum antibacterial agents against drug-resistant pathogens.

In Silico Drug Repositioning for Chagas Disease

Chagas disease is an infectious tropical disease included within the group of neglected tropical diseases. Though historically endemic to Latin America, it has lately spread to high-income countries due to human migration. At present, there are only two available drugs, nifurtimox and benznidazole, approved for this treatment, both with considerable side-effects (which often result in treatment interruption) and limited efficacy in the chronic stage of the disease in adults. Drug repositioning involves finding novel therapeutic indications for known drugs, including approved, withdrawn, abandoned and investigational drugs. It is today a broadly applied approach to develop innovative medications, since indication shifts are built on existing safety, ADME and manufacturing information, thus greatly shortening development timeframes. Drug repositioning has been signaled as a particularly interesting strategy to search for new therapeutic solutions for neglected and rare conditions, which traditionally present limited commercial interest and are mostly covered by the public sector and not-for-profit initiatives and organizations. Here, we review the applications of computer-aided technologies as systematic approaches to drug repositioning in the field of Chagas disease. In silico screening represents the most explored approach, whereas other rational methods such as network-based and signature-based approximations have still not been applied.

Identification of a C2-symmetric diol based human immunodeficiency virus protease inhibitor targeting Zika virus NS2B-NS3 protease

Zika virus (ZIKV) is an emerging mosquito-borne flavivirus and infection by ZIKV Asian lineage is known to cause fetal brain anomalies and Guillain-Barrés syndrome. The WHO declared ZIKV a global public health emergency in 2016. However, currently neither vaccines nor antiviral prophylaxis/treatments are available. In this study, we report the identification of a C2-symmetric diol-based Human immunodeficiency virus type-1 (HIV) protease inhibitor active against ZIKV NS2B-NS3 protease. The compound, referred to as 9b, was identified by in silico screening of a library of 6265 protease inhibitors. Molecular dynamics (MD) simulation studies revealed that compound 9b formed a stable complex with ZIKV protease. Interaction analysis of compound 9b's binding pose from the cluster analysis of MD simulations trajectories predicted that 9b mostly interacted with ZIKV NS3. Although designed as an aspartyl protease inhibitor, compound 9b was found to inhibit ZIKV serine protease in vitro with IC₅₀ = 143.25 ± 5.45 µM, in line with the in silico results. Additionally, linear interaction energy method (LIE) was used to estimate binding affinities of compounds 9b and 86 (a known panflavivirus peptide hybrid with IC₅₀ = 1.64 ± 0.015 µM against ZIKV protease). The LIE method correctly predicted the binding affinity of compound 86 to be lower than that of 9b, proving to be superior to the molecular docking methods in scoring and ranking compounds. Since most of the reported ZIKV protease inhibitors are positively charged peptide-hybrids, with our without electrophilic warheads, compound 9b represents a less polar and more drug-like non-peptide hit compound useful for further optimization.Communicated by Ramaswamy Sarma.

In silico chemical library screening and experimental validation of novel compounds with potential varroacide activities

The mite Varroa destructor is an ectoparasite and has been identified as a major cause of worldwide honey bee colony losses. The use of yearly treatments for the control of varroosis is the most common answer to prevent collapses of honey bee colonies due to the mite. However, the number of effective acaricides is small and the mite tends to become resistant to these few active molecules. In this study, we have been looking for a new original varroacide treatment inhibiting selectively Varroa destructor AChE (vdAChE) with respect to Apis mellifera AChE (amAChE). To do this an original drug design methodology was used applying virtual screening of the CERMN chemolibrary, starting from a vdAChE homology sequence model. By combining the in silico screening with in vitro experiments, two promising compounds were found. In vitro tests of AChE inhibition for both species have confirmed good selectivity toward the mite vdAChE. Moreover, an in vivo protocol was performed and highlighted a varroacide activity without acute consequences on honey bee survival. The two compounds discovered have the potential to become new drug leads for the development of new treatments against the mite varroa. The method described here clearly shows the potential of a drug-design approach to develop new solutions to safeguard honey bee health.

FeptideDB: A web application for new bioactive peptides from food protein

BACKGROUND

Bioactive peptides derived from food are important sources for alternative medicine and possess therapeutic activity. Several biochemical methods have been achieved to isolate bioactive peptides from food, which are tedious and time consuming. In silico methods are an alternative process to reduce cost and time with respect to bioactive peptide production. In this paper, FeptideDB was used to collect bioactive peptide (BP) data from both published research articles and available bioactive peptide databases. FeptideDB was developed to assist in forecasting bioactive peptides from food by combining peptide cleavage tools and database matching. Furthermore, this application was able to predict the potential of cleaved peptides from 'enzyme digestion module' to identify new ACE (angiotensin converting enzyme) inhibitors using an automatic molecular docking approach.

RESULTS

The FeptideDB web application contains tools for generating all possible peptides cleaved from input protein by various available enzymes. This database was also used for analysis and visualization to assist in bioactive peptide discovery. One module of FeptideDB has the ability to create 3-dimensional peptide structures to further predict inhibitors for the target protein, ACE (angiotensin converting enzyme).

CONCLUSIONS

FeptideDB is freely available to researchers who are interested in exploring bioactive peptides. The FeptideDB interface is easy to use, allowing users to rapidly retrieve data based on desired search criteria. FeptideDB is freely available at http://www4g.biotec.or.th/FeptideDB/. Ultimately, FeptideDB is a computational aid for assessing peptide bioactivities.

Combining ligand- and structure-based in silico methods for the identification of natural product-based inhibitors of Akt1

The traditional method of drug discovery process has been surpassed by a rational approach where computer-aided drug designing plays a vital role in the identification of leads from large compound databases. Further, natural products have an important role in drug discovery as these have been the source of most active ingredients of medicines. Herein, in silico structure- and ligand-based approaches have been applied to screen in-house IIIM natural product repository for Akt1 (serine/threonine protein kinases) which is a well-known therapeutic target for cancer due to its overexpression and preventing the cells from undergoing apoptosis. Combined ligand-based and structure-based strategies were applied on to the existing library comprising of about 700 pure natural products, and the compounds identified from screening were biologically evaluated for Akt1 inhibition using Akt1 kinase activity assay. Fourteen promising compounds showed significant inhibition at 500 nM through in vitro screening, and from them, eight were new for Akt1 inhibition. Through the MD studies of Akt1 with the most active compound IN00145, it was inferred that Lys179, Glu191, Glu228, Ala230, Glu234 and Asp292 are the important amino acid residues which provide stability to the Akt1-IN00145 complex. Lead optimization studies were also performed around the actives to design better and selective inhibitors for Akt1. The results emphasized the successful application of virtual screening to identify new Akt1 inhibitor scaffolds that can be developed into a drug candidate in drug discovery programme.

Identification of a novel DGKα inhibitor for XLP-1 therapy by virtual screening

As part of an effort to identify druggable diacylglycerol kinase alpha (DGKα) inhibitors, we used an insilico approach based on chemical homology with the two commercially available DGKα inhibitors R59022 and R59949. Ritanserin and compound AMB639752 emerged from the screening of 127 compounds, showing an inhibitory activity superior to the two commercial inhibitors, being furthermore specific for the alpha isoform of diacylglycerol kinase. Interestingly, AMB639752 was also devoid of serotoninergic activity. The ability of both ritanserin and AMB639752, by inhibiting DGKα in intact cells, to restore restimulation induced cell death (RICD) in SAP deficient lymphocytes was also tested. Both compounds restored RICD at concentrations lower than the two previously available inhibitors, indicating their potential use for the treatment of X-Iinked lymphoproliferative disease 1 (XLP-1), a rare genetic disorder in which DGKα activity is deregulated.

Molecular features characterizing non-peptide selectivity to the human B1 and B2 bradykinin receptors

Bradykinin is produced in response to inflammation, trauma, burns, shock, allergy and some cardiovascular diseases. Actions of this peptide are mediated through two different G-protein coupled receptors, named B1 and B2 that have different pharmacological characteristics. The former is up-regulated during inflammation episodes or tissue trauma whereas, the latter is constitutively expressed in a variety of cell types. In a previous work we have characterized the molecular features that explain the observed structure-activity results for both receptors by means of molecular modeling studies, using diverse ligands for both receptors. These results were summarized in the form of two different pharmacophores that provided new insights to be used for the design of novel molecules with antagonistic profile. In the present work, we compare these pharmacophores to understand the features that characterize ligand selectivity to the two bradykinin receptors. The study shows that most of the residues involved in the binding pocket are similar in both receptors and consequently are the pharmacophores obtained. The main difference between the two pharmacophores remains on point #5 that involves a polar moiety for the B1 receptor and an aromatic ring for the B2 receptor. Accordingly, analysis of the prospective bound conformation of several non-selective small molecule ligands of the bradykinin receptors permits to conclude that fulfilment of point#5 is a requirement to produce selective ligands. However, the study also shows that this is a necessary condition only, since ligands need also to be bulky enough to avoid binding to these receptors in diverse poses. These results provide new insights for a better understanding of the molecular features that ligands are required to exhibit to be selective bradykinin ligands.

Towards good correlation between fragment molecular orbital interaction energies and experimental IC50 for ligand binding: A case study of p38 MAP kinase

We describe several procedures for the preprocessing of fragment molecular orbital (FMO) calculations on p38 mitogen-activated protein (MAP) kinase and discuss the influence of the procedures on the protein–ligand interaction energies represented by inter-fragment interaction energies (IFIEs). The correlation between the summation of IFIEs for a ligand and amino acid residues of protein (IFIE-sum) and experimental affinity values (IC₅₀) was poor when considered for the whole set of protein–ligand complexes. To improve the correlation for prediction of ligand binding affinity, we carefully classified data set by the ligand charge, the DFG-loop state (DFG-in/out loop), which is characteristic of kinase, and the scaffold of ligand. The correlation between IFIE-sums and the activity values was examined using the classified data set. As a result, it was confirmed that there was a selected data set that showed good correlation between IFIE-sum and activity value by appropriate classification. In addition, we found that the differences in protonation and hydrogen orientation caused by subtle differences in preprocessing led to a relatively large difference in IFIE values. Further, we also examined the effect of structure optimization with different force fields. It was confirmed that the difference in the force field had no significant effect on IFIE-sum. From the viewpoint of drug design using FMO calculations, various investigations on IFIE-sum in this research, such as those regarding several classifications of data set and the different procedures of structural preparation, would be expected to provide useful knowledge for improvement of prediction ability about the ligand binding affinity.

Molecular docking analysis of phytoconstituent from Momordica charantia with Guanylate Cyclase catalytic domain

Soluble guanylate cyclase (sGC) is a type of lyase enzyme with profoundly increasing importance in treatments of cardiovascular and neurodegenerative disorders. Modulation of sGC activity demonstrated beneficial effects against Parkinson's disease by reducing glutamate excitotoxicity. It is of interest to evaluate the pharmacological activity of Momordica charantia phytoconstituent (DGalacturonic acid) and ODQ with catalytic domain of sGC enzyme, using Autodock version 4.2 programs. Docking results revealed the binding ability of ODQ at the allosteric sites of sGC. D-galacturonic acid also shows binding interaction at the same allosteric sites in the catalytic domain of sGC like ODQ. Results show that both the ligands have efficient binding to THR 474 amino acid residue of beta 1 subunit of the enzyme. The drug likeliness score further implies the suitability of D-Galacturonic acid as a drug-like molecule. The binding property of ODQ and D-Galacturonic acid with the catalytic domain help to inhibit sGC activity having pharmacological effects. Moreover, ODQ interaction with heme site of sGC is already known while its interaction with the catalytic domain is shown in this report.

Modern Approaches for the Discovery of Anti-Infectious Drugs for the Treatment of Neglected Diseases

Neglected diseases comprise a number of infectious diseases historically endemic to low- and middle-income countries, though recently they have spread to high-income countries due to human migrations. In the past, pharmaceutical companies have shown hesitant to invest in these health conditions, due to the limited return on investment. As a result, the role of the academic sector and not-for-profit organizations in the discovery of new drugs for neglected diseases has been particularly relevant. Here, we review recent applications of modern drug discovery technologies in the field of neglected diseases, including high-throughput screening, in silico screening and computer-aided drug design. The suitability and perspectives of each approach are discussed depending on the context, along with the technology and translational gaps influencing them.

Integrating Experimental and In Silico HTS in the Discovery of Inhibitors of Protein-Nucleic Acid Interactions

Discovery of novel tool compounds and drug leads against a range of unorthodox protein targets has pushed both experimental screening methodologies as well as the field of structure-based design to the limit in recent years. Increasingly, it has been recognized that some of the most desirable targets for the development of small-molecule effectors are actually protein-protein and protein-nucleic acid interactions. There are numerous nontrivial challenges to pursuing small-molecule lead compounds directed toward PPIs and PNIs: relatively shallow cavities, large surface areas that are natively complexed to macromolecules, complex patterns of interstitial waters, a paucity of "hot spots," large conformational changes upon ligand binding, etc. Although there have been some notable successes targeting PPIs in the last decade, there has been distinctly less success in the realm of targeting PNIs. This chapter focuses on an approach, successfully applied by our group to address the challenge of gaining traction on the PPI target RAD52, which is a protein that binds both single-stranded and double-stranded DNA, and is an anticancer target for certain types of cancer. There are many approaches to tackling the difficult problems of finding effective small molecules that disrupt PPIs and PNIs, but the methods presented here offer a series of elegant solutions, which integrate experimental HTS, biophysical methods, docking, and molecular dynamics in a powerful way. Additionally, the structural knowledge gained from these studies provides a means for rationally understanding what features lead to ligand affinity in these fascinating and highly unorthodox pockets.

Computational Design and Synthesis of Novel Fluoro-Analogs of Combretastatins A-4 and A-1

Combretastatin A-1 (CA-1) and combretastatin A-4 (CA-4) isolated from the African bush willow Combretum caffrum are highly potent tubulin polymerization inhibitors, possessing strong antitumor activities because of their vascular disrupting properties. Extensive SAR studies have been done for CA-4 analogs. Because of poor solubility, water-soluble prodrugs of CA-4 and CA-1 have been developed, which are currently in human clinical trials. Fluorine plays an important role in the current drug discovery and development due to its unique properties. Thus, several fluorine-containing analogs of CA-4/CA-1 have been studied. However, no analogs, which have a CF₃O-, CF₂HO- or CF₃- group instead of the 4'-methoxy group in the B ring, have been investigated. Therefore, we set out to design and synthesize those novel fluoro-analogs of CA-4/CA-1. For the design of the new analogs, we took a structure-based design approach based on the X-ray crystal structure of colchicine-tubulin complex (PDB: 4O2B) and computational docking analysis using the AutoDock Vina program. A library of novel fluoro-analogs of CA-4/CA-1 was generated and their docking energy scores obtained. It was found that those novel fluoro-analogs exhibited better docking energy scores than CA-4/CA-1. Also, docking poses of all of these fluoro-analogs were virtually superimposable and very good fit to the colchine binding site. Among 15 compounds designed and analyzed, we have synthesized 5 compounds and evaluated their cytotoxicity against drug-sensitive and multidrug-resistant cancer cell lines. All fluoro-analogs exhibited strong cytotoxicity even against multidrug-resistant cell line. However, the critical activity of this class of compounds is its vascular disrupting activity. Thus, further biological evaluations are warranted for those novel fluoro-analogs of CA-4/CA-1.